IoT-based methods and systems for monitoring and purifying factory wastewater quality.

Abstract

This invention provides a method and system for monitoring and purifying factory wastewater based on the Internet of Things (IoT). Based on the discharge status of factory wastewater, it adjusts the detection actions of distributed water quality sensors to achieve timely and comprehensive monitoring of wastewater, providing reliable data for wastewater purification. From the monitoring data of the distributed water quality sensors, it extracts pollutant content data and wastewater flow rate data during the wastewater's flow process. This generates a pollutant flow and diffusion model of the wastewater during its flow, facilitating accurate IoT-controlled water purification operations to ensure timely and thorough purification. Furthermore, when the water purification unit is at its operational limit, it adjusts the purification operation to prevent prolonged overload and purification failure. This maximizes the continuity and reliability of wastewater purification while providing comprehensive and accurate monitoring.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) monitoring, and more particularly to IoT-based methods and systems for monitoring and purifying factory wastewater. Background Technology

[0002] Factories generate wastewater during operation. To prevent the continuous accumulation of wastewater within the factory, it is necessary to discharge the wastewater and simultaneously purify it. Existing factory wastewater purification systems directly perform pre-defined purification operations on the discharged wastewater. However, these systems do not fully consider the wastewater's quality status, resulting in incomplete purification. Furthermore, they do not approach the purification equipment's processing limits, easily leading to inadequate purification. They also lack comprehensive and accurate water quality monitoring of the discharged wastewater and cannot guarantee continuous and reliable purification. Summary of the Invention

[0003] The purpose of this invention is to provide a method and system for monitoring and purifying factory wastewater based on the Internet of Things (IoT). Based on the discharge status of factory wastewater, it adjusts the detection actions of distributed water quality sensors to achieve timely and comprehensive monitoring of wastewater, providing reliable data for wastewater purification. From the monitoring data of the distributed water quality sensors, it extracts pollutant content data and wastewater flow rate data during the wastewater's flow process. This generates a pollutant flow and diffusion model of the wastewater during its flow, facilitating accurate IoT-controlled water purification operations to ensure timely and thorough purification. Furthermore, when the water purification unit is at its operational limit, it adjusts the purification operation to prevent the unit from operating under overload conditions for extended periods, thus avoiding purification failure. This maximizes the continuity and reliability of wastewater purification while providing comprehensive and accurate monitoring.

[0004] This invention is achieved through the following technical solution:

[0005] IoT-based methods for monitoring and purifying factory wastewater include:

[0006] Based on the discharge status of factory wastewater, detection action commands are sent to distributed water quality sensors;

[0007] The monitoring data from the distributed water quality sensor is analyzed to obtain the flow status data of the factory wastewater; the factory wastewater flow data includes the pollutant content data and wastewater flow rate data during the flow process after the factory wastewater is discharged.

[0008] Based on the flow state data of the factory wastewater, a pollutant flow and diffusion model is generated regarding the discharge of the factory wastewater;

[0009] Based on the pollutant flow and diffusion model, control commands are sent to the water purification terminal via the Internet of Things to determine the purification operation of the water purification terminal on the factory wastewater.

[0010] Based on the operational data of the purification process and the discharge data of the factory wastewater, it is determined whether the water purification end is in its working limit state; and when it is in its working limit state, the purification operation of the water purification end is adjusted.

[0011] Optionally, based on the discharge status of the factory wastewater, detection action commands are sent to the distributed water quality sensors, including:

[0012] Based on the discharge start-up time distribution information of factory wastewater, a trigger action command is sent to the distributed water quality sensors located in the wastewater discharge path so that the distributed water quality sensors enter the corresponding water quality and water flow detection mode.

[0013] Based on the discharge flow rate of the factory wastewater, a detection frequency adjustment action command is sent to the distributed water quality sensors located in the wastewater discharge path, so that the distributed water quality sensors adjust the water quality detection frequency and / or water flow detection frequency of the factory wastewater flowing in the wastewater discharge path.

[0014] The monitoring data from the distributed water quality sensors are analyzed to obtain the flow status data of the factory wastewater, including:

[0015] The water quality monitoring data and water flow monitoring data from the distributed water quality sensor are analyzed to obtain pollutant content data and wastewater flow rate data of the factory wastewater during its flow along the wastewater discharge path; wherein, the pollutant content data includes pollutant concentration distribution data along the length of the wastewater discharge path; and the wastewater flow rate data includes wastewater flow velocity distribution data along the length of the wastewater discharge path.

[0016] Optionally, based on the flow state data of the factory wastewater, a pollutant flow and diffusion model is generated regarding the discharge of the factory wastewater, including:

[0017] The pollutant concentration distribution data and sewage flow velocity distribution data along the length of the sewage discharge path are analyzed and processed to generate a pollutant flow and diffusion model corresponding to the flow of the factory sewage along the sewage discharge path after it is discharged; wherein, the pollutant flow and diffusion model is used to characterize the diffusion trend of pollutants inside the factory sewage along the sewage discharge path;

[0018] Based on the pollutant flow and diffusion model, control commands are sent to the water purification terminal via the Internet of Things to determine the purification operation of the water purification terminal on the factory wastewater, including:

[0019] Based on the pollutant flow and diffusion model, the volume information of the wastewater portion with pollutant concentration greater than or equal to a preset concentration threshold within the wastewater discharge path and the time information of its arrival at the water purification end are predicted.

[0020] Based on the time information, the retention time of the factory wastewater from the wastewater discharge path by the water purification end is determined; based on the volume information, the weight of disinfectant material injected into the retained factory wastewater by the water purification end is determined.

[0021] Optionally, based on the operational data of the purification operation and the discharge data of the factory wastewater, it is determined whether the water purification end is in a working limit state; and when it is in a working limit state, the purification operation of the water purification end is adjusted, including:

[0022] Based on the amount of water purified per unit time and the amount of wastewater discharged from the factory per unit time, it is determined whether the water purification end is at its working limit.

[0023] When the water purification end is at its working limit, the amount of factory wastewater retained by the water purification end during each purification operation is adjusted.

[0024] The IoT-based factory wastewater quality monitoring and purification system includes:

[0025] The water quality sensor control module is used to send detection action commands to the distributed water quality sensors based on the discharge status of factory wastewater.

[0026] The monitoring data analysis module is used to analyze the monitoring data from the distributed water quality sensor to obtain the flow status data of the factory wastewater; the factory wastewater flow data includes pollutant content data and wastewater flow rate data during the flow process after the factory wastewater is discharged.

[0027] The pollutant diffusion model construction module is used to generate a pollutant flow and diffusion model after the factory wastewater is discharged, based on the factory wastewater flow state data.

[0028] The water purification operation determination module is used to send control commands to the water purification terminal via the Internet of Things based on the pollutant flow and diffusion model, and to determine the purification operation of the water purification terminal on the factory wastewater.

[0029] The water purification operation adjustment module is used to determine whether the water purification end is in a working limit state based on the actual operation data of the purification operation and the actual discharge data of the factory wastewater; and when it is in a working limit state, to adjust the purification operation of the water purification end.

[0030] Optionally, the water quality sensor control module is used to send detection action commands to the distributed water quality sensors based on the discharge status of the factory wastewater, including:

[0031] Based on the discharge start-up time distribution information of factory wastewater, a trigger action command is sent to the distributed water quality sensors located in the wastewater discharge path so that the distributed water quality sensors enter the corresponding water quality and water flow detection mode.

[0032] Based on the discharge flow rate of the factory wastewater, a detection frequency adjustment action command is sent to the distributed water quality sensors located in the wastewater discharge path, so that the distributed water quality sensors adjust the water quality detection frequency and / or water flow detection frequency of the factory wastewater flowing in the wastewater discharge path.

[0033] The monitoring data analysis module is used to analyze the monitoring data from the distributed water quality sensor to obtain the flow status data of the factory wastewater; the factory wastewater flow data includes pollutant content data and wastewater flow rate data during the flow process after the factory wastewater is discharged, including:

[0034] The water quality monitoring data and water flow monitoring data from the distributed water quality sensor are analyzed to obtain pollutant content data and wastewater flow rate data of the factory wastewater during its flow along the wastewater discharge path; wherein, the pollutant content data includes pollutant concentration distribution data along the length of the wastewater discharge path; and the wastewater flow rate data includes wastewater flow velocity distribution data along the length of the wastewater discharge path.

[0035] Optionally, the pollutant diffusion model building module is used to generate a pollutant flow and diffusion model after the factory wastewater is discharged, based on the factory wastewater flow state data, including:

[0036] The pollutant concentration distribution data and sewage flow velocity distribution data along the length of the sewage discharge path are analyzed and processed to generate a pollutant flow and diffusion model corresponding to the flow of the factory sewage along the sewage discharge path after it is discharged; wherein, the pollutant flow and diffusion model is used to characterize the diffusion trend of pollutants inside the factory sewage along the sewage discharge path;

[0037] The water purification operation determination module is used to send control commands to the water purification terminal via the Internet of Things based on the pollutant flow and diffusion model, and to determine the purification operation of the water purification terminal on the factory wastewater, including:

[0038] Based on the pollutant flow and diffusion model, the volume information of the wastewater portion with pollutant concentration greater than or equal to a preset concentration threshold within the wastewater discharge path and the time information of its arrival at the water purification end are predicted.

[0039] Based on the time information, the retention time of the factory wastewater from the wastewater discharge path by the water purification end is determined; based on the volume information, the weight of disinfectant material injected into the retained factory wastewater by the water purification end is determined.

[0040] Optionally, the water purification operation adjustment module is used to determine whether the water purification end is in a working limit state based on the actual operation data of the purification operation and the actual discharge data of the factory wastewater; and when it is in a working limit state, to adjust the purification operation of the water purification end, including:

[0041] Based on the amount of water purified per unit time and the amount of wastewater discharged from the factory per unit time, it is determined whether the water purification end is at its working limit.

[0042] When the water purification end is at its working limit, the amount of factory wastewater retained by the water purification end during each purification operation is adjusted.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] The IoT-based method and system for monitoring and purifying factory wastewater provides this application. Based on the discharge status of factory wastewater, it adjusts the detection actions of distributed water quality sensors to achieve timely and comprehensive monitoring of wastewater, providing reliable data for wastewater purification. From the monitoring data of the distributed water quality sensors, it extracts pollutant content data and wastewater flow rate data during the wastewater's flow process. This generates a pollutant flow and diffusion model of the wastewater during its flow, facilitating accurate IoT control of the water purification terminal to implement matched purification operations, ensuring timely and thorough purification of the factory wastewater. Furthermore, when the water purification terminal is at its operational limit, it adjusts the purification operation to prevent the terminal from operating under overload conditions for extended periods, thus avoiding purification failure. Under comprehensive and accurate wastewater monitoring, it maximizes the continuity and reliability of wastewater purification. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0046] Figure 1 A schematic diagram of the process for monitoring and purifying factory wastewater based on the Internet of Things provided by the present invention.

[0047] Figure 2 This is a schematic diagram of the structure of the IoT-based factory wastewater quality monitoring and purification system provided by the present invention. Detailed Implementation

[0048] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, it should be noted that, for ease of description, only the parts relevant to this application are shown in the accompanying drawings, not the entire structure. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this application.

[0049] The terms “comprising” and “having”, and any variations thereof, used in this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the steps or units listed, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus.

[0050] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0051] Please see Figure 1 As shown, an embodiment of this application provides a method for monitoring and purifying factory wastewater quality based on the Internet of Things, including:

[0052] Based on the discharge status of factory wastewater, detection action commands are sent to distributed water quality sensors;

[0053] The monitoring data from the distributed water quality sensors are analyzed to obtain the flow status data of the factory wastewater; the factory wastewater flow data includes the pollutant content data and wastewater flow rate data during the flow process after the factory wastewater is discharged.

[0054] Based on the flow state data of factory wastewater, a model for the flow and diffusion of pollutants after the factory wastewater is discharged is generated.

[0055] Based on the pollutant flow and diffusion model, control commands are sent to the water purification terminal via the Internet of Things to determine the purification operation of the water purification terminal on the factory wastewater.

[0056] Based on the actual operation data of the purification operation and the actual discharge data of the factory wastewater, it is determined whether the water purification end is in the working limit state; and when it is in the working limit state, the purification operation of the water purification end is adjusted.

[0057] The beneficial effects of the above embodiments are as follows: The IoT-based factory wastewater quality monitoring and purification method adjusts the detection actions of distributed water quality sensors based on the discharge status of factory wastewater, achieving timely and comprehensive monitoring of wastewater and providing reliable data for wastewater purification. From the monitoring data of the distributed water quality sensors, pollutant content data and wastewater flow rate data during the flow process of factory wastewater are extracted. This generates a pollutant flow and diffusion model of factory wastewater during its flow process, facilitating accurate IoT control of the water purification terminal to implement matched purification operations for factory wastewater, ensuring timely and thorough purification. Furthermore, when the water purification terminal is at its operational limit, the purification operation is adjusted to avoid the water purification terminal being under overload for extended periods, leading to water purification failure. Under comprehensive and accurate monitoring of wastewater, the method maximizes the continuity and reliability of wastewater purification.

[0058] In another embodiment, based on the discharge status of the factory wastewater, a detection action command is sent to a distributed water quality sensor, including:

[0059] Based on the distribution information of the start time of the factory wastewater discharge, a trigger action command is sent to the distributed water quality sensors located in the wastewater discharge path so that the distributed water quality sensors can enter the corresponding water quality and water flow detection modes.

[0060] Based on the discharge flow rate of the factory wastewater, a detection frequency adjustment action command is sent to the distributed water quality sensors located in the wastewater discharge path, so that the distributed water quality sensors adjust the water quality detection frequency and / or water flow detection frequency of the factory wastewater flowing in the wastewater discharge path.

[0061] Analyzing monitoring data from distributed water quality sensors yields data on the flow status of factory wastewater, including:

[0062] Analyzing water quality monitoring data and water flow monitoring data from distributed water quality sensors yields pollutant content data and wastewater flow rate data during the flow of factory wastewater along the wastewater discharge path. The pollutant content data includes pollutant concentration distribution data along the length of the wastewater discharge path, while the wastewater flow rate data includes wastewater flow velocity distribution data along the length of the wastewater discharge path.

[0063] The beneficial effects of the above embodiments are that, in actual wastewater treatment operations, the wastewater generated during factory operation is directly discharged to the water purification end through a dedicated sewage pipe, where it is purified and disinfected. The sewage pipe provides a dedicated wastewater discharge path, and its inner wall is equipped with distributed water quality sensors. These sensors include several water quality sensing units located at different positions on the inner wall of the pipe. Each sensing unit includes a pollutant sensor and a water flow sensor. The pollutant sensor detects the concentration of pollutants within the wastewater at its location, while the water flow sensor detects the flow rate of the wastewater at its location. The water purification end includes an interception tank and water purification and disinfection equipment. The interception tank acts as a buffer to intercept and buffer wastewater from the sewage pipe, while the water purification and disinfection equipment disinfects and purifies the wastewater in the interception tank. In practice, based on the distribution information of the factory's wastewater discharge start-up time, i.e., the distribution of the discharge start time points corresponding to the factory's wastewater discharge, trigger commands are sent to the distributed water quality sensors in real time. This allows the distributed water quality sensors to simultaneously detect water quality and water flow while the factory discharges wastewater, ensuring real-time detection of wastewater transported within the wastewater discharge path. Furthermore, the factory discharges different volumes of wastewater according to its production capacity; that is, the amount of wastewater discharged is not constant but can increase or decrease. The larger the wastewater discharge flow rate, the greater the flow velocity of the wastewater in the discharge pipe. Therefore, to ensure accurate wastewater monitoring and the reliability of the wastewater monitoring data, a monitoring frequency adjustment command needs to be sent to the distributed water quality sensors. This increases the water quality detection frequency and / or water flow detection frequency of each pollutant sensor and / or each water flow sensor in the distributed water quality sensors, thereby increasing the amount of wastewater data detected in the discharge pipe. Then, the water quality monitoring data (such as pollutant concentration data) and water flow monitoring data (such as sewage flow velocity data) from the distributed water quality sensors are analyzed to obtain the pollutant concentration distribution data and sewage flow velocity distribution data along the length of the sewage discharge path, thereby enabling precise monitoring of the sewage quality and flow status along the sewage discharge path.

[0064] In another embodiment, based on the flow state data of factory wastewater, a model for the flow and diffusion of pollutants after the factory wastewater is discharged is generated, including:

[0065] The data on pollutant concentration distribution and wastewater flow velocity distribution along the length of the wastewater discharge path are analyzed and processed to generate a pollutant flow and diffusion model corresponding to the flow of factory wastewater along the wastewater discharge path after it is discharged. The pollutant flow and diffusion model is used to characterize the diffusion trend of pollutants inside the factory wastewater along the wastewater discharge path.

[0066] Based on a pollutant flow and diffusion model, control commands are sent to the water purification terminal via the Internet of Things (IoT) to determine the purification operations of the water purification terminal on the factory wastewater, including:

[0067] Based on the pollutant flow and diffusion model, the volume information of the sewage portion with pollutant concentration greater than or equal to the preset concentration threshold and the time information of reaching the water purification end are predicted within the sewage discharge path.

[0068] Based on time information, the retention time of factory wastewater from the wastewater discharge path at the water purification end is determined; based on volume information, the weight of disinfectant material injected into the retained factory wastewater at the water purification end is determined.

[0069] The beneficial effects of the above embodiments are as follows: In practical operation, based on the pollutant concentration distribution data and sewage flow velocity distribution data along the length of the sewage discharge path, a deep learning model is trained to obtain a pollutant flow and diffusion model corresponding to the flow along the sewage discharge path. This pollutant flow and diffusion model can be used to characterize the diffusion trend of pollutants within the factory sewage along the sewage discharge path, that is, to characterize the distribution trend of pollutant concentration in different intervals along the length of the sewage discharge path. Furthermore, using the pollutant flow and diffusion model, the pollutant concentration in different parts of the sewage flowing within the sewage discharge path is predicted, and the portion of sewage with a pollutant concentration greater than or equal to a preset concentration threshold is taken as the pollutant accumulation peak portion within the sewage discharge path. This allows for the prediction of the volume information of the pollutant accumulation peak portion and the time information required for it to reach the water purification end along the sewage discharge path. This, in turn, determines the interception operation time of the factory sewage from the sewage discharge path at the water purification end and the weight of disinfectant material (such as chlorine-containing disinfectant powder) injected into the intercepted factory sewage at the water purification end, ensuring that the water purification end can accurately intercept and fully disinfect the sewage.

[0070] In another embodiment, based on the actual operation data of the purification operation and the actual discharge data of the factory wastewater, it is determined whether the water purification end is in a working limit state; and when it is in a working limit state, the purification operation of the water purification end is adjusted, including:

[0071] Based on the amount of water purified per unit time and the amount of wastewater discharged from the factory per unit time, determine whether the water purification end is at its working limit.

[0072] When the water purification end is at its working limit, adjust the amount of wastewater retained by the water purification end during each purification operation.

[0073] The beneficial effect of the above embodiments is that by comparing the amount of water purified in the purification operation per unit time with the amount of factory wastewater discharged per unit time, if the amount of water purified in the purification operation per unit time is less than the amount of factory wastewater discharged per unit time, it is determined that the water purification end is in the working limit state. At this time, the amount of factory wastewater intercepted by the water purification end during each purification operation is reduced, so that the water purification end can fully disinfect and purify the intercepted wastewater.

[0074] Please see Figure 2 As shown, an embodiment of this application provides an IoT-based factory wastewater quality monitoring and purification system, which includes:

[0075] The water quality sensor control module is used to send detection action commands to the distributed water quality sensors based on the discharge status of factory wastewater.

[0076] The monitoring data analysis module is used to analyze monitoring data from distributed water quality sensors to obtain wastewater flow status data. Wastewater flow data includes pollutant content data and wastewater flow rate data during the flow process after wastewater discharge.

[0077] The pollutant diffusion model building module is used to generate a pollutant flow and diffusion model after the factory wastewater is discharged, based on the flow state data of the factory wastewater.

[0078] The water purification operation determination module is used to send control commands to the water purification terminal via the Internet of Things based on the pollutant flow and diffusion model, and determine the purification operation of the water purification terminal on the factory wastewater.

[0079] The water purification operation adjustment module is used to determine whether the water purification end is in a working limit state based on the actual operation data of the purification operation and the actual discharge data of the factory wastewater; and when it is in a working limit state, it adjusts the purification operation of the water purification end.

[0080] The beneficial effects of the above embodiments are that the IoT-based factory wastewater quality monitoring and purification system adjusts the detection actions of distributed water quality sensors based on the discharge status of factory wastewater, achieving timely and comprehensive monitoring of wastewater and providing reliable data for wastewater purification. From the monitoring data of the distributed water quality sensors, it extracts pollutant content data and wastewater flow rate data during the flow of factory wastewater. This generates a pollutant flow and diffusion model of the factory wastewater during its flow, facilitating accurate IoT control of the water purification terminal to implement matched purification operations, ensuring timely and thorough purification of the factory wastewater. Furthermore, when the water purification terminal is at its operational limit, it adjusts the purification operation to prevent the water purification terminal from being overloaded for extended periods, thus avoiding purification failure. Under comprehensive and accurate monitoring of wastewater, it maximizes the continuity and reliability of wastewater purification.

[0081] In another embodiment, the water quality sensor control module is used to send detection action commands to the distributed water quality sensors based on the discharge status of the factory wastewater, including:

[0082] Based on the distribution information of the start time of the factory wastewater discharge, a trigger action command is sent to the distributed water quality sensors located in the wastewater discharge path so that the distributed water quality sensors can enter the corresponding water quality and water flow detection modes.

[0083] Based on the discharge flow rate of the factory wastewater, a detection frequency adjustment action command is sent to the distributed water quality sensors located in the wastewater discharge path, so that the distributed water quality sensors adjust the water quality detection frequency and / or water flow detection frequency of the factory wastewater flowing in the wastewater discharge path.

[0084] The monitoring data analysis module is used to analyze monitoring data from distributed water quality sensors to obtain wastewater flow status data. This wastewater flow data includes pollutant content data and flow rate data during the wastewater's flow process after discharge.

[0085] Analyzing water quality monitoring data and water flow monitoring data from distributed water quality sensors yields pollutant content data and wastewater flow rate data during the flow of factory wastewater along the wastewater discharge path. The pollutant content data includes pollutant concentration distribution data along the length of the wastewater discharge path, while the wastewater flow rate data includes wastewater flow velocity distribution data along the length of the wastewater discharge path.

[0086] The beneficial effects of the above embodiments are that, in actual wastewater treatment operations, the wastewater generated during factory operation is directly discharged to the water purification end through a dedicated sewage pipe, where it is purified and disinfected. The sewage pipe provides a dedicated wastewater discharge path, and its inner wall is equipped with distributed water quality sensors. These sensors include several water quality sensing units located at different positions on the inner wall of the pipe. Each sensing unit includes a pollutant sensor and a water flow sensor. The pollutant sensor detects the concentration of pollutants within the wastewater at its location, while the water flow sensor detects the flow rate of the wastewater at its location. The water purification end includes an interception tank and water purification and disinfection equipment. The interception tank acts as a buffer to intercept and buffer wastewater from the sewage pipe, while the water purification and disinfection equipment disinfects and purifies the wastewater in the interception tank. In practice, based on the distribution information of the factory's wastewater discharge start-up time, i.e., the distribution of the discharge start time points corresponding to the factory's wastewater discharge, trigger commands are sent to the distributed water quality sensors in real time. This allows the distributed water quality sensors to simultaneously detect water quality and water flow while the factory discharges wastewater, ensuring real-time detection of wastewater transported within the wastewater discharge path. Furthermore, the factory discharges different volumes of wastewater according to its production capacity; that is, the amount of wastewater discharged is not constant but can increase or decrease. The larger the wastewater discharge flow rate, the greater the flow velocity of the wastewater in the discharge pipe. Therefore, to ensure accurate wastewater monitoring and the reliability of the wastewater monitoring data, a monitoring frequency adjustment command needs to be sent to the distributed water quality sensors. This increases the water quality detection frequency and / or water flow detection frequency of each pollutant sensor and / or each water flow sensor in the distributed water quality sensors, thereby increasing the amount of wastewater data detected in the discharge pipe. Then, the water quality monitoring data (such as pollutant concentration data) and water flow monitoring data (such as sewage flow velocity data) from the distributed water quality sensors are analyzed to obtain the pollutant concentration distribution data and sewage flow velocity distribution data along the length of the sewage discharge path, thereby enabling precise monitoring of the sewage quality and flow status along the sewage discharge path.

[0087] In another embodiment, the pollutant diffusion model building module is used to generate a pollutant flow and diffusion model after the factory wastewater is discharged, based on the factory wastewater flow state data, including:

[0088] The data on pollutant concentration distribution and wastewater flow velocity distribution along the length of the wastewater discharge path are analyzed and processed to generate a pollutant flow and diffusion model corresponding to the flow of factory wastewater along the wastewater discharge path after it is discharged. The pollutant flow and diffusion model is used to characterize the diffusion trend of pollutants inside the factory wastewater along the wastewater discharge path.

[0089] The water purification operation determination module is used to send control commands to the water purification terminal via the Internet of Things based on a pollutant flow and diffusion model, and to determine the purification operation of the water purification terminal on the factory wastewater, including:

[0090] Based on the pollutant flow and diffusion model, the volume information of the sewage portion with pollutant concentration greater than or equal to the preset concentration threshold and the time information of reaching the water purification end are predicted within the sewage discharge path.

[0091] Based on time information, the retention time of factory wastewater from the wastewater discharge path at the water purification end is determined; based on volume information, the weight of disinfectant material injected into the retained factory wastewater at the water purification end is determined.

[0092] The beneficial effects of the above embodiments are as follows: In practical operation, based on the pollutant concentration distribution data and sewage flow velocity distribution data along the length of the sewage discharge path, a deep learning model is trained to obtain a pollutant flow and diffusion model corresponding to the flow along the sewage discharge path. This pollutant flow and diffusion model can be used to characterize the diffusion trend of pollutants within the factory sewage along the sewage discharge path, that is, to characterize the distribution trend of pollutant concentration in different intervals along the length of the sewage discharge path. Furthermore, using the pollutant flow and diffusion model, the pollutant concentration in different parts of the sewage flowing within the sewage discharge path is predicted, and the portion of sewage with a pollutant concentration greater than or equal to a preset concentration threshold is taken as the pollutant accumulation peak portion within the sewage discharge path. This allows for the prediction of the volume information of the pollutant accumulation peak portion and the time information required for it to reach the water purification end along the sewage discharge path. This, in turn, determines the interception operation time of the factory sewage from the sewage discharge path at the water purification end and the weight of disinfectant material (such as chlorine-containing disinfectant powder) injected into the intercepted factory sewage at the water purification end, ensuring that the water purification end can accurately intercept and fully disinfect the sewage.

[0093] In another embodiment, the water purification operation adjustment module is used to determine whether the water purification end is in a working limit state based on the actual operation data of the purification operation and the actual discharge data of the factory wastewater; and when it is in a working limit state, to adjust the purification operation of the water purification end, including:

[0094] Based on the amount of water purified per unit time and the amount of wastewater discharged from the factory per unit time, determine whether the water purification end is at its working limit.

[0095] When the water purification end is at its working limit, adjust the amount of wastewater retained by the water purification end during each purification operation.

[0096] The beneficial effect of the above embodiments is that by comparing the amount of water purified in the purification operation per unit time with the amount of factory wastewater discharged per unit time, if the amount of water purified in the purification operation per unit time is less than the amount of factory wastewater discharged per unit time, it is determined that the water purification end is in the working limit state. At this time, the amount of factory wastewater intercepted by the water purification end during each purification operation is reduced, so that the water purification end can fully disinfect and purify the intercepted wastewater.

[0097] In summary, the IoT-based method and system for monitoring and purifying factory wastewater quality adjusts the detection actions of distributed water quality sensors based on the discharge status of factory wastewater, achieving timely and comprehensive monitoring of wastewater and providing reliable data for wastewater purification. From the monitoring data of the distributed water quality sensors, pollutant content and flow rate data of the factory wastewater during its flow process are extracted. This generates a pollutant flow and diffusion model of the factory wastewater during its flow, facilitating accurate IoT-controlled water purification operations to ensure timely and thorough purification. Furthermore, when the water purification unit is at its operational limit, the purification operation is adjusted to prevent it from operating under overload conditions for extended periods, thus avoiding purification failure. This comprehensive and accurate monitoring of wastewater maximizes the continuity and reliability of wastewater purification.

[0098] The above is only one specific embodiment of the present invention, and any improvements made based on the concept of the present invention shall be considered within the scope of protection of the present invention.

Claims

1. A method for monitoring and purifying factory wastewater quality based on the Internet of Things, characterized in that, include: Based on the discharge status of factory wastewater, detection action commands are sent to distributed water quality sensors; The monitoring data from the distributed water quality sensor is analyzed to obtain the flow status data of the factory wastewater; the flow status data of the factory wastewater includes the pollutant content data and the wastewater flow rate data during the flow process after the factory wastewater is discharged. Based on the flow state data of the factory wastewater, a pollutant flow and diffusion model is generated regarding the discharge of the factory wastewater; Based on the pollutant flow and diffusion model, control commands are sent to the water purification terminal via the Internet of Things to determine the purification operation of the water purification terminal on the factory wastewater. Based on the operational data of the purification operation and the discharge data of the factory wastewater, it is determined whether the water purification end is in a working limit state; and when it is in a working limit state, the purification operation of the water purification end is adjusted. Specifically, based on the flow state data of the factory wastewater, a pollutant flow and diffusion model is generated regarding the discharge of the factory wastewater, including: The pollutant concentration distribution data and sewage flow velocity distribution data along the length of the sewage discharge path are analyzed and processed to generate a pollutant flow and diffusion model corresponding to the flow of the factory sewage along the sewage discharge path after it is discharged; wherein, the pollutant flow and diffusion model is used to characterize the diffusion trend of pollutants inside the factory sewage along the sewage discharge path; Based on the pollutant flow and diffusion model, control commands are sent to the water purification terminal via the Internet of Things to determine the purification operation of the water purification terminal on the factory wastewater, including: Based on the pollutant flow and diffusion model, the volume information of the wastewater portion with pollutant concentration greater than or equal to a preset concentration threshold within the wastewater discharge path and the time information of its arrival at the water purification end are predicted. Based on the time information, the retention time of the factory wastewater from the wastewater discharge path by the water purification end is determined; based on the volume information, the weight of disinfectant material injected into the retained factory wastewater by the water purification end is determined.

2. The method for monitoring and purifying factory wastewater based on the Internet of Things as described in claim 1, characterized in that: Based on the discharge status of factory wastewater, detection action commands are sent to distributed water quality sensors, including: Based on the discharge start-up time distribution information of factory wastewater, a trigger action command is sent to the distributed water quality sensors located in the wastewater discharge path so that the distributed water quality sensors enter the corresponding water quality and water flow detection mode. Based on the discharge flow rate of the factory wastewater, a detection frequency adjustment action command is sent to the distributed water quality sensors located in the wastewater discharge path, so that the distributed water quality sensors adjust the water quality detection frequency and / or water flow detection frequency of the factory wastewater flowing in the wastewater discharge path. The monitoring data from the distributed water quality sensors are analyzed to obtain the flow status data of the factory wastewater, including: The water quality monitoring data and water flow monitoring data from the distributed water quality sensor are analyzed to obtain pollutant content data and wastewater flow rate data of the factory wastewater during its flow along the wastewater discharge path; wherein, the pollutant content data includes pollutant concentration distribution data along the length of the wastewater discharge path; and the wastewater flow rate data includes wastewater flow velocity distribution data along the length of the wastewater discharge path.

3. The method for monitoring and purifying factory wastewater based on the Internet of Things as described in claim 1, characterized in that: Based on the operational data of the purification process and the discharge data of the factory wastewater, determine whether the water purification terminal is at its operational limit; and when it is at its operational limit, adjust the purification operation of the water purification terminal, including: Based on the amount of water purified per unit time and the amount of wastewater discharged from the factory per unit time, it is determined whether the water purification end is at its working limit. When the water purification end is at its working limit, the amount of factory wastewater retained by the water purification end during each purification operation is adjusted.

4. A factory wastewater quality monitoring and purification system based on the Internet of Things, characterized in that, include: The water quality sensor control module is used to send detection action commands to the distributed water quality sensors based on the discharge status of factory wastewater. The monitoring data analysis module is used to analyze the monitoring data from the distributed water quality sensor to obtain the flow status data of the factory wastewater; the flow status data of the factory wastewater includes the pollutant content data and the wastewater flow rate data during the flow process after the factory wastewater is discharged. The pollutant diffusion model construction module is used to generate a pollutant flow and diffusion model after the factory wastewater is discharged, based on the factory wastewater flow state data. The water purification operation determination module is used to send control commands to the water purification terminal via the Internet of Things based on the pollutant flow and diffusion model, and to determine the purification operation of the water purification terminal on the factory wastewater. The water purification operation adjustment module is used to determine whether the water purification end is in a working limit state based on the actual operation data of the purification operation and the actual discharge data of the factory wastewater; and when it is in a working limit state, to adjust the purification operation of the water purification end. The pollutant diffusion model construction module is used to generate a pollutant flow and diffusion model after the factory wastewater is discharged, based on the factory wastewater flow state data, including: The pollutant concentration distribution data and sewage flow velocity distribution data along the length of the sewage discharge path are analyzed and processed to generate a pollutant flow and diffusion model corresponding to the flow of the factory sewage along the sewage discharge path after it is discharged; wherein, the pollutant flow and diffusion model is used to characterize the diffusion trend of pollutants inside the factory sewage along the sewage discharge path; The water purification operation determination module is used to send control commands to the water purification terminal via the Internet of Things based on the pollutant flow and diffusion model, and to determine the purification operation of the water purification terminal on the factory wastewater, including: Based on the pollutant flow and diffusion model, the volume information of the wastewater portion with pollutant concentration greater than or equal to a preset concentration threshold within the wastewater discharge path and the time information of its arrival at the water purification end are predicted. Based on the time information, the retention time of the factory wastewater from the wastewater discharge path by the water purification end is determined; based on the volume information, the weight of disinfectant material injected into the retained factory wastewater by the water purification end is determined.

5. The IoT-based factory wastewater quality monitoring and purification system as described in claim 4, characterized in that: The water quality sensor control module is used to send detection action commands to the distributed water quality sensors based on the discharge status of the factory wastewater, including: Based on the discharge start-up time distribution information of factory wastewater, a trigger action command is sent to the distributed water quality sensors located in the wastewater discharge path so that the distributed water quality sensors enter the corresponding water quality and water flow detection mode. Based on the discharge flow rate of the factory wastewater, a detection frequency adjustment action command is sent to the distributed water quality sensors located in the wastewater discharge path, so that the distributed water quality sensors adjust the water quality detection frequency and / or water flow detection frequency of the factory wastewater flowing in the wastewater discharge path. The monitoring data analysis module is used to analyze the monitoring data from the distributed water quality sensor to obtain the flow status data of the factory wastewater; the factory wastewater flow data includes pollutant content data and wastewater flow rate data during the flow process after the factory wastewater is discharged, including: The water quality monitoring data and water flow monitoring data from the distributed water quality sensor are analyzed to obtain pollutant content data and wastewater flow rate data of the factory wastewater during its flow along the wastewater discharge path; wherein, the pollutant content data includes pollutant concentration distribution data along the length of the wastewater discharge path; and the wastewater flow rate data includes wastewater flow velocity distribution data along the length of the wastewater discharge path.

6. The IoT-based factory wastewater quality monitoring and purification system as described in claim 4, characterized in that: The water purification operation adjustment module is used to determine whether the water purification end is in a working limit state based on the real-time operation data of the purification operation and the real-time discharge data of the factory wastewater. And when the water is at its operating limit, adjust the purification operation of the water purification end, including: Based on the amount of water purified per unit time and the amount of wastewater discharged from the factory per unit time, it is determined whether the water purification end is at its working limit. When the water purification end is at its working limit, the amount of factory wastewater retained by the water purification end during each purification operation is adjusted.

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